From GPS to semantic data: how and why—a framework for enriching smartphone trajectories

Abstract

AbstractDeriving human behaviour from smartphone location data is a multitask enrichment process that can be of value in behavioural studies. Optimising the algorithmic details of the enrichment tasks has shaped the current advances in the literature. However, the lack of a processing framework built around those advances complicates the planning for implementing the enrichment. This work fulfils the need for a holistic and integrative view that comprehends smartphone-specific requirements and challenges to help researchers plan the implementation. We propose a structural framework from a systematic literature review conducted to pinpoint the main challenges and requirements of research on enriching location data. We classify findings based on the enrichment task and integrate them accordingly into workflows that facilitate the task’s implementation. These workflows help researchers better streamline their implementations of the enrichment process and analyse errors within and across tasks. Moreover, researchers can integrate the presented findings with the proposed opportunities to better predict the impact of their research.